Subjective image fidelity
metric based on bit allocation of the human visual system in the DCT domain

Until now, subjective image distortion
measures have partially used diverse empirical facts concerning human perception:
non-linear perception of luminance, masking of the impairments by a highly
textured surround, linear filtering by the threshold frequency response
of the visual system, and non-linear post-filtering amplitude corrections
in the frequency domain.

In this work, we develop a frequency and
contrast dependent metric in the DCT domain using a fully non-linear and
suprathreshold contrast perception model: the Information Allocation
Function (IAF) of the visual system. It is derived from experimental
data about frequency and contrast incremental thresholds and it is consistent
with the reported noise adaptation of the visual system frequency response.
Exhaustive psychophysical comparison with the results of other subjective
metrics confirms that our model deals with a wider range of distortions
more accurately than previously reported metrics. The developed metric
can, therefore, be incorporated in the design of image coding algorithms
as a closer approximation of human assessment of image quality.